210 citations · 516 across the 9 of their papers we have counts for
10 papers
Limited-angle tomographic reconstruction of dense layered objects by dynamical machine learning
Iksung Kang, Alexandre Goy, George Barbastathis
Limited-angle tomography of strongly scattering quasi-transparent objects is a challenging, highly ill-posed problem with practical implications in medical and biological imaging,…
Learning to Synthesize: Robust Phase Retrieval at Low Photon counts
Mo Deng, Shuai Li, Alexandre Goy +2
The quality of inverse problem solutions obtained through deep learning [Barbastathis et al, 2019] is limited by the nature of the priors learned from examples presented during the…
Low Photon Budget Phase Retrieval with Perceptual Loss Trained Deep Neural Networks
Mo Deng, Alexandre Goy, Shuai Li +2
Deep neural networks (DNNs) are efficient solvers for ill-posed problems and have been shown to outperform classical optimization techniques in several computational imaging proble…
High-Resolution Limited-Angle Phase Tomography of Dense Layered Objects Using Deep Neural Networks
Alexandre Goy, Girish Rughoobur, Shuai Li +3
We present a Machine Learning-based method for tomographic reconstruction of dense layered objects, with range of projection angles limited to 10. Whereas previous ap…
Low Photon Count Phase Retrieval Using Deep Learning
Alexandre Goy, Kwabena Arthur, Shuai Li +1
Imaging systems' performance at low light intensity is affected by shot noise, which becomes increasingly strong as the power of the light source decreases. In this paper we experi…
Imaging thick samples with optical tomography
Alexandre Goy, Morteza H. Shoreh, JooWon Lim +2
Optical diffraction tomography (ODT), initially described in the seminal paper of Emil Wolf [Opt. Comm., 1(4), 153-156 (1969)], has received renewed attention recently. The vast ma…